Raspberry Pi Computer Vision Programming -Second Edition: Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3

Pajankar, Ashwin


Key Features

  • Explore the potential of computer vision with Raspberry Pi and Python programming
  • Perform computer vision tasks such as image processing and manipulation using OpenCV and Raspberry Pi
  • Discover easy-to-follow examples and screenshots to implement popular computer vision techniques and applications

Book Description

Raspberry Pi is one of the popular single-board computers of our generation. All the major image processing and computer vision algorithms and operations can be implemented easily with OpenCV on Raspberry Pi. This updated second edition is packed with cutting-edge examples and new topics, and covers the latest versions of key technologies such as Python 3, Raspberry Pi, and OpenCV. This book will equip you with the skills required to successfully design and implement your own OpenCV, Raspberry Pi, and Python-based computer vision projects.

At the start, you'll learn the basics of Python 3, and the fundamentals of single-board computers and NumPy. Next, you'll discover how to install OpenCV 4 for Python 3 on Raspberry Pi, before covering major techniques and algorithms in image processing, manipulation, and computer vision. By working through the steps in each chapter, you'll understand essential OpenCV features. Later sections will take you through creating graphical user interface (GUI) apps with GPIO and OpenCV. You'll also learn to use the new computer vision library, Mahotas, to perform various image processing operations. Finally, you'll explore the Jupyter Notebook and how to set up a Windows computer and Ubuntu for computer vision.

By the end of this book, you'll be able to confidently build and deploy computer vision apps.

What you will learn

  • Set up a Raspberry Pi for computer vision applications
  • Perform basic image processing with libraries such as NumPy, Matplotlib, and OpenCV
  • Demonstrate arithmetical, logical, and other operations on images
  • Work with a USB webcam and the Raspberry Pi Camera Module
  • Implement low-pass and high-pass filters and understand their applications in image processing
  • Cover advanced techniques such as histogram equalization and morphological transformations
  • Create GUI apps with Python 3 and OpenCV
  • Perform machine learning with K-means clustering and image quantization

Who this book is for

This book is for beginners as well as experienced Raspberry Pi and Python 3 enthusiasts who are looking to explore the amazing world of computer vision. Working knowledge of the Python 3 programming language is assumed.



  • 使用Raspberry Pi和Python編程探索計算機視覺的潛力

  • 使用OpenCV和Raspberry Pi執行圖像處理和操作等計算機視覺任務

  • 通過易於跟隨的示例和屏幕截圖,了解實現流行的計算機視覺技術和應用的方法


Raspberry Pi是我們這一代流行的單板計算機之一。使用OpenCV在Raspberry Pi上可以輕鬆實現所有主要的圖像處理和計算機視覺算法和操作。這本更新的第二版充滿了尖端的示例和新主題,並涵蓋了Python 3、Raspberry Pi和OpenCV等關鍵技術的最新版本。本書將使您具備成功設計和實施自己的基於OpenCV、Raspberry Pi和Python的計算機視覺項目所需的技能。

首先,您將學習Python 3的基礎知識,以及單板計算機和NumPy的基礎知識。接下來,您將了解如何在Raspberry Pi上安裝Python 3的OpenCV 4,然後涵蓋圖像處理、操作和計算機視覺中的主要技術和算法。通過逐章進行的步驟,您將了解基本的OpenCV功能。後面的章節將帶您通過使用GPIO和OpenCV創建圖形用戶界面(GUI)應用程序。您還將學習使用新的計算機視覺庫Mahotas執行各種圖像處理操作。最後,您將探索Jupyter Notebook以及如何為計算機視覺設置Windows計算機和Ubuntu。



  • 為計算機視覺應用程序設置Raspberry Pi

  • 使用NumPy、Matplotlib和OpenCV等庫進行基本圖像處理

  • 在圖像上執行算術、邏輯和其他操作

  • 使用USB攝像頭和Raspberry Pi攝像頭模塊進行工作

  • 實現低通和高通濾波器,並了解它們在圖像處理中的應用

  • 涵蓋直方圖均衡化和形態學變換等高級技術

  • 使用Python 3和OpenCV創建GUI應用程序

  • 使用K-means聚類和圖像量化進行機器學習


本書適合初學者和有經驗的Raspberry Pi和Python 3愛好者,他們希望探索令人驚嘆的計算機視覺世界。假設您具備Python 3編程語言的工作知識。


  1. Introduction to Computer Vision and Raspberry Pi
  2. Prepare Raspberry Pi for Computer Vision
  3. Programming with Python 3, GPIO, NumPy, and Matplotlib
  4. Getting started with Computer Vision
  5. Basics of Image Processing
  6. Colorspaces, Transformations, and Thresholding
  7. Let's Make Some Noise
  8. High Pass Filters and Feature Detection
  9. Image Restoration, Quantization, and Depth Map
  10. Histograms, Contours, and Morphological Transformations
  11. Real-life Computer Vision Applications
  12. Wrapping Up with Mahotas and Jupyter Notebook
  13. Appendix


  1. 計算機視覺和樹莓派介紹

  2. 為計算機視覺準備樹莓派

  3. 使用Python 3、GPIO、NumPy和Matplotlib進行編程

  4. 開始使用計算機視覺

  5. 圖像處理基礎知識

  6. 色彩空間、轉換和閾值處理

  7. 製造一些噪音

  8. 高通濾波器和特徵檢測

  9. 圖像恢復、量化和深度圖

  10. 直方圖、輪廓和形態轉換

  11. 實際應用計算機視覺

  12. 使用Mahotas和Jupyter Notebook結束

  13. 附錄